Search results for: action learning

Authors: Songul Cinaroglu

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Regional planning in health has gained speed for developing countries in recent years. In Turkey, 89 different Public Hospital Unions (PHUs) were conducted based on provincial levels. In this study technical efficiencies of 89 PHUs were examined by using Data Envelopment Analysis (DEA) and machine learning techniques by dividing them into two clusters in terms of similarities of input and output indicators. Number of beds, physicians and nurses determined as input variables and number of outpatients, inpatients and surgical operations determined as output indicators. Before performing DEA, PHUs were grouped into two clusters. It is seen that the first cluster represents PHUs which have higher population, demand and service density than the others. The difference between clusters was statistically significant in terms of all study variables (p ˂ 0.001). After clustering, DEA was performed for general and for two clusters separately. It was found that 11% of PHUs were efficient in general, additionally 21% and 17% of them were efficient for the first and second clusters respectively. It is seen that PHUs, which are representing urban parts of the country and have higher population and service density, are more efficient than others. Random forest decision tree graph shows that number of inpatients is a determinative factor of efficiency of PHUs, which is a measure of service density. It is advisable for public health policy makers to use statistical learning methods in resource planning decisions to improve efficiency in health care.

Keywords: public hospital unions, efficiency, data envelopment analysis, random forest

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Authors: Enes Caliskan, Hatice Camgoz Akdag

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There is no doubt that humanity needs to realize the sustainability problems in the world and take serious action regarding that. All members of the United Nations adopted the 2030 Agenda for Sustainable Development, the most comprehensive study on sustainability internationally, in 2015. The summary of the study is 17 sustainable development goals. It covers everything about sustainability, such as environment, society and governance. The use of Information and Communication Technology (ICT), such as the Internet, mobile phones, and satellites, is essential for tackling the main issues facing sustainable development. Hence, the contributions of 3 major ICT companies to the sustainable development goals are assessed in this study. Quality Function Deployment (QFD) is utilized as a methodology for this study. Since QFD is an excellent instrument for comparing businesses on relevant subjects, a House of Quality must be established to complete the QFD application. In order to develop a House of Quality, the demanded qualities (voice of the customer) and quality characteristics (technical requirements) must first be determined. UN SDGs are used as demanded qualities. Quality characteristics are derived from annual sustainability and corporate social responsibility reports of ICT companies. The companies' efforts, as indicated by the QFD results, are concentrated on the use of recycled raw materials and recycling, reducing GHG emissions through energy saving and improved connectivity, decarbonizing the value chain, protecting the environment and water resources by collaborating with businesses that have completed CDP water assessments and paying attention to reducing water consumption, ethical business practices, and reducing inequality. The evaluations of the three businesses are found to be very similar when they are compared. The small differences between the companies are usually about the region they serve. Efforts made by the companies mostly concentrate on responsible consumption and production, life below water, climate action, and sustainable cities and community goals. These efforts include improving connectivity in needed areas for providing access to information, education and healthcare.

Keywords: multi-criteria decision-making, sustainable supply chain risk, supply chain agility, quality function deployment, Sustainable development goals

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Authors: M. Rezki, A. Belaidi

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This paper deals with a method of learning to solve a real problem in biomedical engineering from a technical study of muscle fatigue. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles (viewpoint: anatomical and physiological). EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain and muscle fatigue in general. In order to study the EMG signal for detecting fatigue in a muscle, we have taken a real problem which touches the tramway conductor the handle bar. For the study, we have used a typical autonomous platform in order to get signals at real time. In our case study, we were confronted with complex problem to do our experiments in a tram. This type of problem is recurring among students. To teach our students the method to solve this kind of problem, we built a similar system. Through this study, we realized a lot of objectives such as making the equipment for simulation, the study of detection of muscle fatigue and especially how to manage a study of biomedical looking.

Keywords: EMG, health platform, conductor’s tram, muscle fatigue

Procedia PDF Downloads 302

Authors: Laura Naka

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The invention of computer writing programs has changed the way of teaching second language writing. This artificial intelligence engine can provide students with feedback on their essays, on their grammatical and spelling errors, convenient writing and editing tools to facilitate student’s writing process. However, it is not yet proved if this technology is helping students to improve their writing skills. There are several programs that are of great assistance for students concerning their writing skills. New technology provides students with different software programs which enable them to be more creative, to express their opinions and ideas in words, pictures and sounds, but at the end main and most correct feedback should be given by their teachers. No matter how new technology affects in writing skills, always comes from their teachers. This research will try to present some of the advantages and disadvantages that new technology has in writing process for students. The research takes place in the University of Gjakova ‘’Fehmi Agani’’ Faculty of Education-Preschool Program. The research aims to provide random sample response by using questionnaires and observation.

Keywords: English language learning, technology, academic writing, teaching L2.

Procedia PDF Downloads 555

Authors: M. Armenteros, A. Domínguez, M. Fernández, A. J. Benítez

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The following paper describes the video database tool used by the Fédération Internationale de Football Association (FIFA) as part of the research project developed in collaboration with the Carlos III University of Madrid. The database project began in 2012, with the aim of creating an educational tool for the training of instructors, referees and assistant referees, and it has been used in all FUTURO III courses since 2013. The platform now contains 3,135 video clips of different match situations from FIFA competitions. It has 1,835 users (FIFA instructors, referees and assistant referees). In this work, the main features of the database are described, such as the use of a search tool and the creation of multimedia presentations and video quizzes. The database has been developed in MySQL, ActionScript, Ruby on Rails and HTML. This tool has been rated by users as "very good" in all courses, which prompt us to introduce it as an ideal tool for any other sport that requires the use of video analysis.

Keywords: assistants referees, cloud computing, e-learning, instructors, FIFA, referees, soccer, video database

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Authors: Nomfundo Ngombane, Topside E. Mathonsi

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Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

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Authors: Kibbeum Na

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Previous gamification research has produced mixed results regarding the effectiveness of gamified learning. One possible explanation for this is that individuals perceive the game elements differently. Cognitive Evaluation Theory posits that external rewards can boost or undermine intrinsic motivation, depending on whether the rewards are perceived as informational or controlling. This research tested the hypothesis that game elements can be perceived as either informational feedback or external reward, and the motivational impact differ accordingly. An experiment was conducted using an educational math puzzle to compare the motivation and performance as a result of different perceived affordances game elements. Participants were primed to perceive the game elements as either informational feedback or external reward, and the duration of an attempt to solve the unsolvable puzzle – amotivation indicator – and the puzzle score – a performance indicator–were measured with the game elements incorporated and then without the game elements. Badges and points were deployed as the main game elements. Results showed that, regardless of priming, a significant decrease in performance occurred when the game elements were removed, whereas the control group who solved non-gamified math puzzles maintained their performance. The undermined performance with gamification removal indicates that learners may perceive some game elements as controlling factors irrespective of the way they are presented. The results of the current study also imply that some game elements are better not being implemented to preserve long-term performance. Further research delving into the extrinsic reward-like nature of game elements and its impact on learning motivation is called for.

Keywords: cognitive Evaluation Theory, game elements, gamification, motivation, motivational affordance, performance

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Authors: S. Probine

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The visual arts have been proven to be a central means through which young children can communicate their ideas, reflect on experience, and construct new knowledge. Despite this, perceptions of, and the degree to which the visual arts are valued within education, vary widely within political, educational, community and family contexts. These differing perceptions informed my doctoral research project, which explored the contextual factors that affect how young children come to value and use the visual arts in their lives and learning. The qualitative methodology of narrative inquiry with inclusion of arts-based methods was most appropriate for this inquiry. Using a sociocultural framework, the stories collected were analysed through the sociocultural theories of Lev Vygotsky as well as the work of Urie Bronfenbrenner, together with postmodern theories about identity formation. The use of arts-based methods such as teacher’s reflective art journals and the collection of images by child participants and their parent/caregivers allowed the research participants to have a significant role in the research. Three early childhood settings at which the visual arts were deeply valued as a meaning-making device in children’s learning, were purposively selected to be involved in the research. At each setting, the study found a unique and complex web of influences and interconnections, which shaped how children utilised the visual arts to mediate their thinking. Although the teachers' practices at all three centres were influenced by sociocultural theories, each settings' interpretations of these theories were unique and resulted in innovative interpretations of the role of the teacher in supporting visual arts learning. These practices had a significant impact on children’s experiences of the visual arts. For many of the children involved in this study, visual art was the primary means through which they learned. The children in this study used visual art to represent their experiences, relationships, to explore working theories, their interests (including those related to popular culture), to make sense of their own and other cultures, and to enrich their imaginative play. This research demonstrates that teachers have fundamental roles in fostering and disseminating the importance of the visual arts within their educational communities.

Keywords: arts-based methods, early childhood education, teacher's visual arts pedagogies, visual arts

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Authors: Lin Xie, Yang Wang

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An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: education, communication, psychology, student learning, language teaching

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Authors: Carlos Joel Tchawouo Mbiada

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At the back of the apartheid era, South Africa embarked on a democratic drive of all its institution underpinned by a social justice perspective to eradicate past injustices. These democratic values based on fundamental human rights and equality informed all rights enshrined in the Constitution of the Republic of South Africa, 1996. This means that all rights are therefore infused by social justice perspective and labour rights are no exception. Labour law is therefore regulated to the extent that it is viewed as too rigid. Hence a call for more flexibility to enhance investment and boost job creation. This view articulated by the Free Market Foundation fell on deaf ears as the opponents believe in what is termed regulated flexibility which affords greater protection to vulnerable workers while promoting business opportunities and investment. The question that this paper seeks to examine is to what extent the regulation of labour law will go to protect employees. This question is prompted by the recent Constitutional Court’s judgment of National Union of Metalworkers of South Africa v Trenstar which barred the employer from employing labour replacement in response to the strike action by its employees. The question whether employers may use replacement labour and have recourse to lock-outs in response to strike action is considered in the context of the dichotomy between the Free market foundation and social justice perspectives which are at loggerheads in the South African collective bargaining process. With the current unemployment rate soaring constantly, the aftermath of the Covid 19 pandemic, the effects of the war in Ukraine and lately the financial burden of load shedding on companies to run their businesses, this paper argues for a policy shift toward deregulation or a lesser state and judiciary intervention. This initiative will relieve the burden on companies to run a viable business while at the same time protecting existing jobs.

Keywords: labour law, replacement labour, right to strike, free market foundation perspective, social justice perspective

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Authors: Yi-Ning Chang

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With the rapid advancement of technology, it has become crucial for educators to adeptly integrate technology into their teaching and develop a robust Computer-Assisted Language Learning (CALL) competency. Addressing this need, the present study adopted a technology-based Lesson Study approach to assess its impact on the CALL competency and professional capabilities of EFL teachers. Additionally, the study delved into teachers' perceptions of the benefits derived from participating in the creation of technologically integrated lesson plans. The iterative process of technology-based Lesson Study facilitated ample peer discussion, enabling teachers to flexibly design and implement lesson plans that incorporate various technological tools. This 15-week study included 10 in- service teachers from a university of science and technology in the central of Taiwan. The collected data included pre- and post- lesson planning scores, pre- and post- TPACK survey scores, classroom observation forms, designed lesson plans, and reflective essays. The pre- and post- lesson planning and TPACK survey scores were analyzed employing a pair-sampled t test; students’ reflective essays were respectively analyzed applying content analysis. The findings revealed that the teachers’ lesson planning ability and CALL competencies were improved. Teachers perceived a better understanding of integrating technology with teaching subjects, more effective teaching skills, and a deeper understanding of technology. Pedagogical implications and future studies are also discussed.

Keywords: CALL, language learning, lesson study, lesson plan

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Authors: Marc Dorval, Marie-Hélène Jobin

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This work presents the various perspectives, dimensions, components and definitions given to quality in the operations management (OM) and healthcare services (HCS) literature in time, highlighting gaps and learning opportunities between the two disciplines through a thorough search into their rich and distinct body of knowledge. Greater and new insights about the general nature of quality are obtained with findings such as in OM, quality has been approached in six fairly distinct paradigms (excellence, value, conformity to specifications, attributes, satisfaction and meeting or exceeding customer expectations), whereas in HCS, two approaches are prominent (Donabedian’s structure, process and outcomes model and Lohr and Schroeder’s circumscribed definition). The two disciplines views on quality seem to have progressed much in parallel with little cross-learning from each other. This work then proposes an encompassing definition of quality as a lever and suggests further research and development avenues for a better use of the concept of quality by academics and practitioners alike toward the goals of greater organizational performance and improved management in healthcare and possibly other service domains.

Keywords: healthcare, management, operations, quality, services

Procedia PDF Downloads 216

Authors: Fangfei Li

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This research was conducted to explore how Chinese overseas students, who rarely received teacher feedback during their undergraduate studies in China, engaged in a different feedback provision context in the UK universities. In particular, this research provides some insights into Chinese students’ perspectives on how they made sense of the teacher feedback they obtained and how they took it on board in their assignments. Research questions in this study are 1) What are Chinese overseas students’ perceptions of teacher feedback on courses in UK higher education? 2) How do they respond to the teacher feedback they obtained? 3) What factors might influence their engagement with teacher feedback? Multiple case studies of five Chinese overseas students in a UK university have been carried out to address the research questions. The main data collection instruments are various types of semi-structured interviews, consisting of background interviews, scenario-based activities, stimulated recall sessions and retrospective interviews. Research findings indicate that student engagement with teacher feedback is a complex learning process incorporating several stages: from initial teacher input to ultimate transformational learning. Apart from students interpreting teachers’ comments/suggestions by themselves, students’ understandings of and responses to teacher feedback could also be influenced by pre-submission guidance, peer discussion, use of exemplars and post-submission discussion with teachers. These are key factors influencing students to make use of teacher feedback. Findings also reveal that the level of students’ reflections on tutor feedback influences the quality of their assignments and even their future learning. To sum up, this paper will discuss the current concepts of teacher feedback in existing studies and research findings of this study from which reconceptualization of teacher feedback has occurred.

Keywords: Chinese students, student engagement, teacher feedback, the UK higher education

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Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

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Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

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Authors: Mohammad Hadi Khorashadi Zadeh, Amin Karkon, Seyd Mohammad Reza Mashhoori ‎

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the technology of Computer audit played a major role in the progress and ‎prospects of a proper application to improve the quality and efficiency of audit ‎work. But due to the technical complexity and the specific risks of computer ‎audit, it should be shown effective in audit and preventive action. Mainly through ‎research in this paper, we proposes the causes of audit risk in a computer ‎environment and the risk of further proposals for measures to control, to some ‎extent reduce the risk of computer audit and improve the audit quality.‎

Keywords: computer auditing, risk, measures to prevent, information technology

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Authors: Pascal Roubides

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The presentation proposed herein describes a research case study of a hybrid application of the competency-based education model best exemplified by Western Governor’s University, within the general temporal confines of an accelerated (8-week) term of a College Algebra course at the author’s institution. A competency-based model was applied to an accelerated online College Algebra course, built as an Open Educational Resources (OER) course, seeking quantifiable evidence of any differences in the academic achievement of students enrolled in the competency-based course and the academic achievement of the current delivery of the same course. Competency-based learning has been gaining in support in recent times and the author’s institution has also been involved in its own efforts to design and develop courses based on this approach. However, it is unknown whether there had been any research conducted to quantify evidence of the effect of this approach against traditional approaches prior to the author’s case study. The research question sought to answer in this experimental quantitative study was whether the online College Algebra curriculum at the author’s institution delivered via an OER-based competency-based model can produce statistically significant improvement in retention and success rates against the current delivery of the same course. Results obtained in this study showed that there is no statistical difference in the retention rate of the two groups. However, there was a statistically significant difference found between the rates of successful completion of students in the experimental group versus those in the control group.

Keywords: competency-based learning, online mathematics, online math education, online courses

Procedia PDF Downloads 117

Authors: Sheryl Bernardo-Hinesley

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Heritage language learners are students who have been raised in a home where a minority language is spoken, who speaks or merely understand the minority heritage language, but to some degree are bilingual in the majority and the heritage language. In view of the rising university enrollment by Hispanics in the United States who have chosen to study Spanish, university language programs are currently faced with challenges of accommodating the language needs of heritage language learners of Spanish. The present study investigates the heritage language perception and language attitudes by heritage language learners of Spanish, as well as their classroom language learning experiences and needs. In order to carry out the study, a qualitative survey was used to gather data from university students. Analysis of students' responses indicates that heritage learners are motivated to learn the heritage language. In relation to the aspects of focus of a language course for heritage learners, results show that the aspects of interest are accent marks and spelling, grammatical accuracy, vocabulary, writing, reading, and culture.

Keywords: heritage language learners, language acquisition, linguistic attitudes, Spanish in the US

Procedia PDF Downloads 191

Authors: Chen-Jung Chen, Yi-Chang Chen

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While traditional virtual reality and augmented reality only allow for small movement learning and cannot provide a truly immersive teaching experience to give it the illusion of movement, the new technology of both content creation and immersive interactive simulation of the metaverse can just reach infinite close to the natural teaching situation. However, the mixed reality virtual classroom of metaverse has not yet explored its theory, and it is rarely implemented in the situational simulation teaching of nursing education. Therefore, in the first year, the study will intend to use grounded theory and case study methods and in-depth interviews with nursing education and information experts. Analyze the interview data to investigate the uniqueness of metaverse development. The proposed analysis will lead to alternative theories and methods for the development of nursing education. In the second year, it will plan to integrate the metaverse virtual situation simulation technology into the alternate teaching strategy in the pediatric nursing technology course and explore the nursing students' use of this teaching method as the construction of personal technology and experience. By leveraging the unique features of distinct teaching platforms and developing processes to deliver alternative teaching strategies in a nursing technology teaching environment. The aim is to increase learning achievements without compromising teaching quality and teacher-student relationships in the post-pandemic era. A descriptive and convergent mixed methods design will be employed. Sixty third-grade nursing students will be recruited to participate in the research and complete the pre-test. The students in the experimental group (N=30) agreed to participate in 4 real-time mixed virtual situation simulation courses in self-practice after class and conducted qualitative interviews after each 2 virtual situation courses; the control group (N=30) adopted traditional practice methods of self-learning after class. Both groups of students took a post-test after the course. Data analysis will adopt descriptive statistics, paired t-tests, one-way analysis of variance, and qualitative content analysis. This study addresses key issues in the virtual reality environment for teaching and learning within the metaverse, providing valuable lessons and insights for enhancing the quality of education. The findings of this study are expected to contribute useful information for the future development of digital teaching and learning in nursing and other practice-based disciplines.

Keywords: metaverse, post-pandemic era, online virtual classroom, immersive teaching

Procedia PDF Downloads 49

Authors: Wang Zhanquan, Yang Zeping, Gu Chunhua, Zhu Fazhi, Guo Weibin

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Recently, Massive Open Online Courses (MOOCs) are becoming the new trend of education. There are many problems under the environment of Database Principle curriculum teaching process in MOOCs, such as teaching ideas and theories which are out of touch with the reality, how to carry out the technical teaching and interactive practice in the MOOCs environment, thus the methods of database course under the environment of MOOCs are proposed. There are three processes to deal with problem solving in the research, which are problems proposed, problems solved, and inductive analysis. The present research includes the design of teaching contents, teaching methods in classroom, flipped classroom teaching mode under the environment of MOOCs, learning flow method and large practice homework. The database designing ability is systematically improved based on the researching methods.

Keywords: problem solving-driven, MOOCs, teaching art, learning flow;

Procedia PDF Downloads 356

Authors: Ehsan Atefi, Michael Grigware

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Respiratory failure secondary to surfactant deficiency resulting from respiratory distress syndrome is considered one major cause of morbidity in preterm infants. Surfactant replacement treatment (SRT) is considered an effective treatment for this disease. Here, we introduce an AI-mediated approach for estimating the distribution of surfactant in the lung airway of a newborn infant during SRT. Our approach implements machine learning to precisely estimate the splitting ratio of a liquid drop during bifurcation at different injection velocities and patient orientations. This technique can be used to calculate the surfactant residue remaining on the airway wall during the surfactant injection process. Our model works by minimizing the pressure drop difference between the two airway branches at each generation, subject to mass and momentum conservation. Our platform can be used to generate feedback for immediately adjusting the velocity of injection and patient orientation during SRT.

Keywords: respiratory failure, surfactant deficiency, surfactant replacement, machine learning

Procedia PDF Downloads 110

Authors: Kittivate Boonyopakorn

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The purposes of this study were to find the English competence of the public health volunteers and to develop the use of their English. The samples for the study were 41 public health village volunteers at Ban Prasukchai, in Thailand. The findings showed that the sum of all scores for the pre-test was 452, while the score for the post-test was 1,080. Therefore, the results of the experiment confirm that the post-test scores (1,080) significantly are higher than the pre-test (452). The mean score (N=41) for the pre-test was 11.02 while the mean score (N=41) for the post-test was 18.10. The standard deviation for the pre-test was 2.734; however, for the post-test it was 1.934. In addition to the experts-evaluated research tools, the results of the evaluation for the structured interviews (IOC) were 1 in value. The evaluation of congruence for the content with learning objectives (IOC) were 0.66 to 1.00 in value. The evaluation of congruence for the pre and post-test with learning objectives (IOC) are 1 in value.

Keywords: finding the English competency, developing public health, village volunteers

Procedia PDF Downloads 437

Authors: Shao-Di Feng, Von-Wun Soo

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To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.

Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning

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Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

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Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

Procedia PDF Downloads 557

Authors: Ciaran Friel, Jerry Suls, Mark Butler, Patrick Robles, Samantha Gordon, Frank Vicari, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate-intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant engagement. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit® fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7 but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by Fitbit for two weeks. In the 8-week intervention phase of the study, participants received each of the four BCTs, in random order, for a two-week period. Text message prompts were delivered daily each morning at a consistent time. All prompts required participant engagement to acknowledge receipt of the BCT message. Engagement is dependent upon the BCT message and may have included recording that a detailed plan for walking has been made or confirmed a daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves to their baseline average step count (self-monitoring, feedback). At the end of each two-week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances, and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. The analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, five days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of an N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

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Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: R. R. Govind

Abstract:

In the digital age, artificial intelligence (AI) is having a significant impact on the rapid changes that cities are experiencing. This study explores the profound impact of AI on urban morphology, especially with regard to promoting friendly design choices. It addresses a significant research gap by examining the real-world effects of integrating AI into urban design and management. The main objective is to outline a framework for integrating AI to transform urban settings. The study employs an urban design framework to effectively navigate complicated urban environments, emphasize the need for urban management, and provide efficient planning and design strategies. Taking Gangtok's informal settlements as a focal point, the study employs AI methodologies such as machine learning, predictive analytics, and generative AI to tackle issues of 'urban informality'. The insights garnered not only offer valuable perspectives but also unveil AI's transformative potential in addressing contemporary urban challenges.

Keywords: urban design, artificial intelligence, urban challenges, machine learning, urban informality

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Authors: George Abu-Aqil, Leah Tsror, Elad Shufan, Shaul Mordechai, Mahmoud Huleihel, Ahmad Salman

Abstract:

Pectobacterium and Dickeya spp which negatively affect a wide range of crops are the main causes of the aggressive diseases of agricultural crops. These aggressive diseases are responsible for a huge economic loss in agriculture including a severe decrease in the quality of the stored vegetables and fruits. Therefore, it is important to detect these pathogenic bacteria at their early stages of infection to control their spread and consequently reduce the economic losses. In addition, early detection is vital for producing non-infected propagative material for future generations. The currently used molecular techniques for the identification of these bacteria at the strain level are expensive and laborious. Other techniques require a long time of ~48 h for detection. Thus, there is a clear need for rapid, non-expensive, accurate and reliable techniques for early detection of these bacteria. In this study, infrared spectroscopy, which is a well-known technique with all its features, was used for rapid detection of Pectobacterium and Dickeya spp. at the strain level. The bacteria were isolated from potato plants and tubers with soft rot symptoms and measured by infrared spectroscopy. The obtained spectra were analyzed using different machine learning algorithms. The performances of our approach for taxonomic classification among the bacterial samples were evaluated in terms of success rates. The success rates for the correct classification of the genus, species and strain levels were ~100%, 95.2% and 92.6% respectively.

Keywords: soft rot enterobacteriaceae (SRE), pectobacterium, dickeya, plant infections, potato, solanum tuberosum, infrared spectroscopy, machine learning

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Authors: Rie Adachi

Abstract:

In Japan, it is required to improve students’ English communicative proficiency and the Education Ministry will start English education for the third grade and upper from year 2020 on. Considering the problems with the educational system, Content and Language Integrated Learning (CLIL) is more appropriate to be employed in elementary schools rather than just introducing English lessons. Effective CLIL takes place in the 4Cs Framework, and different strategies are used in various activities, such as arts and crafts, bodily expression, singing, playing roles, etc. After a CLIL workshop for local teachers focused on the 4Cs, the writer conducted a survey of the 36 participants using a questionnaire and found that they did not know the word CLIL, but seemed to have an interest after attending the workshop. The writer concluded that researchers and practitioners need to spread awareness of the 4Cs framework, to apply CLIL into Japanese educational context, to provide CLIL teacher training program and so on, in order to practice CLIL in Japanese elementary schools and nurture students with a global mindset.

Keywords: CLIL, 4Cs, homeroom teachers, intercultural understanding

Procedia PDF Downloads 157

Authors: Joy Aworookoroh

Abstract:

Writing is one of the active skills in language learning. Students of English as a foreign language are expected to write efficiently and proficiently in the language; however, there are usually challenges to optimal performance and competence in writing. Errors, on the other hand, in a foreign language learning situation are more positive than negative as they provide the basis for solving the limitations of the students. This paper investigates the situation in the Department of English, Taraba State University Jalingo. Students are administered a descriptive writing test across different levels of study. The target students are multilingual with an L1 of either Kuteb, Hausa or Junkun languages. The essays are accessed to identify the different kinds of errors in them alongside the classification of the order. Errors of correctness, clarity, engagement, and delivery were identified. However, the study identified that the degree of errors reduces alongside the experience and exposure of the students to an EFL classroom.

Keywords: errors, writings, descriptive essay, multilingual

Procedia PDF Downloads 46